Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review
In recent years, deep convolutional neural networks (CNNs) have shown record-shattering
performance in a variety of computer vision problems, such as visual object recognition …
performance in a variety of computer vision problems, such as visual object recognition …
Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives
Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of
Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast …
Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast …
HyperDense-Net: a hyper-densely connected CNN for multi-modal image segmentation
Recently, dense connections have attracted substantial attention in computer vision
because they facilitate gradient flow and implicit deep supervision during training …
because they facilitate gradient flow and implicit deep supervision during training …
Automated segmentation of tissues using CT and MRI: a systematic review
Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …
body using computed tomography and magnetic resonance imaging has been rapidly …
[HTML][HTML] What is new in computer vision and artificial intelligence in medical image analysis applications
J Olveres, G González, F Torres… - … imaging in medicine …, 2021 - ncbi.nlm.nih.gov
Computer vision and artificial intelligence applications in medicine are becoming
increasingly important day by day, especially in the field of image technology. In this paper …
increasingly important day by day, especially in the field of image technology. In this paper …
[HTML][HTML] Applying image-based food-recognition systems on dietary assessment: a systematic review
Dietary assessment can be crucial for the overall well-being of humans and, at least in some
instances, for the prevention and management of chronic, life-threatening diseases. Recall …
instances, for the prevention and management of chronic, life-threatening diseases. Recall …
[HTML][HTML] Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features
Sub-cortical brain structure segmentation in Magnetic Resonance Images (MRI) has
attracted the interest of the research community for a long time as morphological changes in …
attracted the interest of the research community for a long time as morphological changes in …
Efficient classification of chronic kidney disease by using multi‐kernel support vector machine and fruit fly optimization algorithm
L Jerlin Rubini, E Perumal - International Journal of Imaging …, 2020 - Wiley Online Library
In recent days, the gigantic generation of medical data from smart healthcare applications
requires the development of big data classification methodologies. Medical data …
requires the development of big data classification methodologies. Medical data …
Artificial intelligence accelerates multi-modal biomedical process: A Survey
The abundance of artificial intelligence AI algorithms and growing computing power has
brought a disruptive revolution to the smart medical industry. Its powerful data abstraction …
brought a disruptive revolution to the smart medical industry. Its powerful data abstraction …
Loss weightings for improving imbalanced brain structure segmentation using fully convolutional networks
Brain structure segmentation on magnetic resonance (MR) images is important for various
clinical applications. It has been automatically performed by using fully convolutional …
clinical applications. It has been automatically performed by using fully convolutional …